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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We believe that the IP addresses from Canada , Russia and Norway are analysis systems of antivirus companies or security researchers .' [/INST] [We:O, believe:O, that:O, the:O, IP:O, addresses:O, from:O, Canada:B-Area, ,:O, Russia:B-Area, and:O, Norway:B-Area, are:O, analysis:O, systems:O, of:O, antivirus:B-Org, companies:I-Org, or:O, security:O, researchers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Overall , the Bookworm infrastructure overlaps with the infrastructure hosting C2 servers used by various attack tools , including FFRAT , Poison Ivy , PlugX , and others .' [/INST] [Overall:O, ,:O, the:O, Bookworm:B-Tool, infrastructure:O, overlaps:O, with:O, the:O, infrastructure:O, hosting:O, C2:O, servers:O, used:O, by:O, various:O, attack:B-OffAct, tools:O, ,:O, including:O, FFRAT:B-Tool, ,:O, Poison:B-Tool, Ivy:I-Tool, ,:O, PlugX:B-Tool, ,:O, and:O, others:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Overall , the Bookworm infrastructure overlaps with the infrastructure hosting C2 servers used by various attack tools , including FFRAT , Poison Ivy , PlugX , and others .' [/INST] [Overall:O, ,:O, the:O, Bookworm:B-Tool, infrastructure:O, overlaps:O, with:O, the:O, infrastructure:O, hosting:O, C2:O, servers:O, used:O, by:O, various:O, attack:B-OffAct, tools:O, ,:O, including:O, FFRAT:B-Tool, ,:O, Poison:B-Tool, Ivy:I-Tool, ,:O, PlugX:B-Tool, ,:O, and:O, others:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Unit 42 enumerated the threat infrastructure related to Bookworm and created a chart to visualize connected entities to its current attack campaign .' [/INST] [Unit:B-SecTeam, 42:I-SecTeam, enumerated:O, the:O, threat:O, infrastructure:O, related:O, to:O, Bookworm:B-Tool, and:O, created:O, a:O, chart:O, to:O, visualize:O, connected:O, entities:O, to:O, its:O, current:O, attack:B-OffAct, campaign:I-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Threat actors have targeted the government of Thailand and delivered the newly discovered Bookworm Trojan since July 2015 .' [/INST] [Threat:O, actors:O, have:O, targeted:O, the:O, government:B-Idus, of:O, Thailand:O, and:O, delivered:O, the:O, newly:O, discovered:O, Bookworm:B-Tool, Trojan:I-Tool, since:O, July:B-Time, 2015:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The actors appear to follow a set playbook , as the observed TTPs are fairly static within each attack in this campaign .' [/INST] [The:O, actors:O, appear:O, to:O, follow:O, a:O, set:O, playbook:O, ,:O, as:O, the:O, observed:O, TTPs:O, are:O, fairly:O, static:O, within:O, each:O, attack:B-OffAct, in:O, this:O, campaign:B-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'So far , Unit 42 has seen infrastructure overlaps with servers hosting C2 servers for samples of the FFRAT , PlugX , Poison Ivy and Scieron Trojans , suggesting that the threat actors use these tools as the payload in their attacks .' [/INST] [So:O, far:O, ,:O, Unit:B-SecTeam, 42:I-SecTeam, has:O, seen:O, infrastructure:O, overlaps:O, with:O, servers:O, hosting:O, C2:O, servers:O, for:O, samples:O, of:O, the:O, FFRAT:B-Tool, ,:O, PlugX:B-Tool, ,:O, Poison:B-Tool, Ivy:I-Tool, and:O, Scieron:B-Tool, Trojans:I-Tool, ,:O, suggesting:O, that:O, the:O, threat:O, actors:O, use:O, these:O, tools:O, as:O, the:O, payload:O, in:O, their:O, attacks:B-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The threat actors have continually used Flash Player installers and Flash slideshows for decoys .' [/INST] [The:O, threat:O, actors:O, have:O, continually:O, used:O, Flash:B-Tool, Player:I-Tool, installers:I-Tool, and:O, Flash:B-Tool, slideshows:I-Tool, for:O, decoys:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The vast majority of systems communicating with Bookworm C2 servers are within the Bangkok metropolitan area where a majority of the government of Thailand exists .' [/INST] [The:O, vast:O, majority:O, of:O, systems:O, communicating:O, with:O, Bookworm:B-Tool, C2:O, servers:O, are:O, within:O, the:O, Bangkok:O, metropolitan:O, area:O, where:O, a:O, majority:O, of:O, the:O, government:B-Idus, of:O, Thailand:O, exists:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Buhtrap has been active since 2014 , however their first attacks against financial institutions were only detected in August 2015 .' [/INST] [Buhtrap:B-HackOrg, has:O, been:O, active:O, since:O, 2014:B-Time, ,:O, however:O, their:O, first:O, attacks:B-OffAct, against:O, financial:B-Org, institutions:I-Org, were:O, only:O, detected:O, in:O, August:B-Time, 2015:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'At the moment , the group is known to target Russian and Ukrainian banks .' [/INST] [At:O, the:O, moment:O, ,:O, the:O, group:O, is:O, known:O, to:O, target:O, Russian:O, and:O, Ukrainian:B-Area, banks:B-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Buhtrap is the first hacker group using a network worm to infect the overall bank infrastructure that significantly increases the difficulty of removing all malicious functions from the network .' [/INST] [Buhtrap:B-HackOrg, is:O, the:O, first:O, hacker:O, group:O, using:O, a:O, network:B-Way, worm:I-Way, to:O, infect:O, the:O, overall:O, bank:B-Idus, infrastructure:O, that:O, significantly:O, increases:O, the:O, difficulty:O, of:O, removing:O, all:O, malicious:O, functions:O, from:O, the:O, network:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Malicious programs intentionally scan for machines with an automated Bank-Customer system of the Central bank of Russia ( further referred to as BCS CBR ) .' [/INST] [Malicious:O, programs:O, intentionally:O, scan:B-Features, for:I-Features, machines:I-Features, with:O, an:O, automated:O, Bank-Customer:O, system:O, of:O, the:O, Central:O, bank:B-Idus, of:O, Russia:B-Area, (:O, further:O, referred:O, to:O, as:O, BCS:O, CBR:O, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'If the document was delivered with macros instead of exploits ( CVE-2012-0158 , CVE-2013-3906 or CVE-2014-1761 ) , then the document contained instructions for enabling macros .' [/INST] [If:O, the:O, document:B-SamFile, was:O, delivered:O, with:O, macros:O, instead:O, of:O, exploits:O, (:O, CVE-2012-0158:B-Exp, ,:O, CVE-2013-3906:B-Exp, or:O, CVE-2014-1761:B-Exp, ):O, ,:O, then:O, the:O, document:O, contained:O, instructions:O, for:O, enabling:O, macros:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We noticed that criminals were spreading Buhtrap using this method from May 2015 to August 2015 .' [/INST] [We:O, noticed:O, that:O, criminals:O, were:O, spreading:O, Buhtrap:B-HackOrg, using:O, this:O, method:O, from:O, May:B-Time, 2015:I-Time, to:O, August:B-Time, 2015:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'It is worth noting that attackers used the same compromised websites to spread Buhtrap as those that had been used for the Corkow Trojan .' [/INST] [It:O, is:O, worth:O, noting:O, that:O, attackers:O, used:O, the:O, same:O, compromised:B-Tool, websites:I-Tool, to:O, spread:O, Buhtrap:B-Tool, as:O, those:O, that:O, had:O, been:O, used:O, for:O, the:O, Corkow:B-Tool, Trojan:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Moreover , they used the same exploit kit Niteris as that in the Corkow case .' [/INST] [Moreover:O, ,:O, they:O, used:O, the:O, same:O, exploit:O, kit:B-Exp, Niteris:I-Exp, as:O, that:O, in:O, the:O, Corkow:B-Tool, case:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Purportedly during one of the first attacks hackers intercepted the mailing list of the Anti-drop , club and created a specific phishing email for its members .' [/INST] [Purportedly:O, during:O, one:O, of:O, the:O, first:O, attacks:B-OffAct, hackers:O, intercepted:O, the:O, mailing:O, list:O, of:O, the:O, Anti-drop:O, ,:O, club:O, and:O, created:O, a:O, specific:O, phishing:B-Way, email:I-Way, for:O, its:O, members:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , it is still widely used , notably in Russia .' [/INST] [However:O, ,:O, it:O, is:O, still:O, widely:O, used:O, ,:O, notably:O, in:O, Russia:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'As noted in our previous blog on Buhtrap , this gang has been actively targeting Russian businesses , mostly through spear-phishing .' [/INST] [As:O, noted:O, in:O, our:O, previous:O, blog:O, on:O, Buhtrap:O, ,:O, this:O, gang:O, has:O, been:O, actively:O, targeting:O, Russian:O, businesses:B-Idus, ,:O, mostly:O, through:O, spear-phishing:B-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'It is thus interesting to see Buhtrap add strategic web compromises to their arsenal .' [/INST] [It:O, is:O, thus:O, interesting:O, to:O, see:O, Buhtrap:O, add:O, strategic:B-Way, web:I-Way, compromises:I-Way, to:O, their:O, arsenal:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The first malware we saw was the lurk downloader , which was distributed on October 26th .' [/INST] [The:O, first:O, malware:O, we:O, saw:O, was:O, the:O, lurk:B-Tool, downloader:I-Tool, ,:O, which:O, was:O, distributed:O, on:O, October:B-Time, 26th:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The executable would install the real Ammyy product , but would also launch a file called either AmmyyService.exe or AmmyySvc.exe which contained the malicious payload .' [/INST] [The:O, executable:O, would:O, install:O, the:O, real:O, Ammyy:O, product:O, ,:O, but:O, would:O, also:O, launch:O, a:O, file:O, called:O, either:O, AmmyyService.exe:B-SamFile, or:O, AmmyySvc.exe:B-SamFile, which:O, contained:O, the:O, malicious:O, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Buhtrap is getting better at disguising the code they inject into compromised websites .' [/INST] [Buhtrap:B-HackOrg, is:O, getting:O, better:O, at:O, disguising:O, the:O, code:O, they:O, inject:O, into:O, compromised:B-Tool, websites:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'With the recent arrests of actors using the Lurk banking trojan , Buhtrap appears to be a likely alternative for actors wishing to target Russian banks and software .' [/INST] [With:O, the:O, recent:O, arrests:O, of:O, actors:O, using:O, the:O, Lurk:B-Tool, banking:I-Tool, trojan:I-Tool, ,:O, Buhtrap:O, appears:O, to:O, be:O, a:O, likely:O, alternative:O, for:O, actors:O, wishing:O, to:O, target:O, Russian:B-Area, banks:B-Idus, and:O, software:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'They have different functions and ways of spreading , but the same purpose — to steal money from the accounts of businesses .' [/INST] [They:O, have:O, different:O, functions:O, and:O, ways:O, of:O, spreading:O, ,:O, but:O, the:O, same:O, purpose:O, —:O, to:O, steal:B-Purp, money:I-Purp, from:O, the:O, accounts:O, of:O, businesses:B-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Our experts have found that cybercriminals are actively focusing on SMBs , and giving particular attention to accountants .' [/INST] [Our:O, experts:O, have:O, found:O, that:O, cybercriminals:O, are:O, actively:O, focusing:O, on:O, SMBs:B-Tool, ,:O, and:O, giving:O, particular:O, attention:O, to:O, accountants:B-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The first encounter with Buhtrap was registered back in 2014 .' [/INST] [The:O, first:O, encounter:O, with:O, Buhtrap:O, was:O, registered:O, back:O, in:O, 2014:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'For now , we can call RTM one of the most active financial Trojans .' [/INST] [For:O, now:O, ,:O, we:O, can:O, call:O, RTM:B-Tool, one:O, of:O, the:O, most:O, active:O, financial:B-Idus, Trojans:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'At that time it was the name of a cybercriminal group that was stealing money from Russian financial establishments — to the tune of at least $150,000 per hit .' [/INST] [At:O, that:O, time:O, it:O, was:O, the:O, name:O, of:O, a:O, cybercriminal:O, group:O, that:O, was:O, stealing:B-Purp, money:I-Purp, from:O, Russian:B-Area, financial:B-Org, establishments:I-Org, —:O, to:O, the:O, tune:O, of:O, at:O, least:O, $150,000:O, per:O, hit:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Buhtrap resurfaced in the beginning of 2017 in the TwoBee campaign , where it served primarily as means of malware delivery .' [/INST] [Buhtrap:O, resurfaced:O, in:O, the:O, beginning:O, of:O, 2017:B-Time, in:O, the:O, TwoBee:B-OffAct, campaign:I-OffAct, ,:O, where:O, it:O, served:O, primarily:O, as:O, means:O, of:O, malware:O, delivery:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'After the source codes of their tools became public in 2016 , the name Buhtrap was used for the financial Trojan .' [/INST] [After:O, the:O, source:O, codes:O, of:O, their:O, tools:O, became:O, public:O, in:O, 2016:B-Time, ,:O, the:O, name:O, Buhtrap:O, was:O, used:O, for:O, the:O, financial:B-Tool, Trojan:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Just like last time , Buhtrap is spreading through exploits embedded in news outlets .' [/INST] [Just:O, like:O, last:O, time:O, ,:O, Buhtrap:O, is:O, spreading:O, through:O, exploits:O, embedded:O, in:O, news:B-Idus, outlets:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Estimating the damages is challenging , but as we learned , the criminals are siphoning off assets in transactions that do not exceed $15,000 each .' [/INST] [Estimating:O, the:O, damages:O, is:O, challenging:O, ,:O, but:O, as:O, we:O, learned:O, ,:O, the:O, criminals:O, are:O, siphoning:B-Purp, off:I-Purp, assets:I-Purp, in:I-Purp, transactions:I-Purp, that:O, do:O, not:O, exceed:O, $15,000:O, each:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'As explained later , we believe this campaign is financially-motivated and that it targets accounting departments in Russian businesses .' [/INST] [As:O, explained:O, later:O, ,:O, we:O, believe:O, this:O, campaign:B-OffAct, is:O, financially-motivated:O, and:O, that:O, it:O, targets:O, accounting:B-Org, departments:I-Org, in:O, Russian:O, businesses:B-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: ', Buhgalter , means , accountant , in Russian .' [/INST] [,:O, Buhgalter:O, ,:O, means:O, ,:O, accountant:O, ,:O, in:O, Russian:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Seeing a campaign like this , inevitably the Anunak/Carbanak documented by Fox-IT and Kaspersky comes to mind .' [/INST] [Seeing:O, a:O, campaign:B-OffAct, like:O, this:O, ,:O, inevitably:O, the:O, Anunak/Carbanak:B-Tool, documented:O, by:O, Fox-IT:B-SecTeam, and:O, Kaspersky:B-SecTeam, comes:O, to:O, mind:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The infection vector is similar , it uses a similar modified mimikatz application , and it uses a third-party remote access tool , changes system settings to allow concurrent RDP sessions , and so on .' [/INST] [The:O, infection:O, vector:O, is:O, similar:O, ,:O, it:O, uses:O, a:O, similar:O, modified:O, mimikatz:B-Tool, application:O, ,:O, and:O, it:O, uses:O, a:O, third-party:B-Tool, remote:I-Tool, access:I-Tool, tool:I-Tool, ,:O, changes:O, system:O, settings:O, to:O, allow:O, concurrent:O, RDP:B-Tool, sessions:O, ,:O, and:O, so:O, on:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The second , aptly titled , kontrakt87.doc , , copies a generic telecommunications service contract from MegaFon , a large Russian mobile phone operator .' [/INST] [The:O, second:O, ,:O, aptly:O, titled:O, ,:O, kontrakt87.doc:B-SamFile, ,:O, ,:O, copies:O, a:O, generic:O, telecommunications:B-Idus, service:I-Idus, contract:O, from:O, MegaFon:B-Org, ,:O, a:O, large:O, Russian:B-Area, mobile:B-Org, phone:I-Org, operator:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In addition to built-in functionalities , the operators of Careto can upload additional modules which can perform any malicious task .' [/INST] [In:O, addition:O, to:O, built-in:O, functionalities:O, ,:O, the:O, operators:O, of:O, Careto:B-SamFile, can:O, upload:B-Features, additional:I-Features, modules:I-Features, which:O, can:O, perform:O, any:O, malicious:O, task:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Careto 's Mask campaign we discovered relies on spear-phishing e-mails with links to a malicious website .' [/INST] [Careto:B-SamFile, 's:O, Mask:B-OffAct, campaign:I-OffAct, we:O, discovered:O, relies:O, on:O, spear-phishing:B-Way, e-mails:I-Way, with:O, links:O, to:O, a:O, malicious:O, website:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Sometimes , the attackers use sub-domains on the exploit websites , to make them seem more legitimate .' [/INST] [Sometimes:O, ,:O, the:O, attackers:O, use:O, sub-domains:B-Tool, on:O, the:O, exploit:O, websites:O, ,:O, to:O, make:O, them:O, seem:O, more:O, legitimate:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'These sub-domains simulate sub-sections of the main newspapers in Spain plus some international ones like the Guardian and the Washington Post .' [/INST] [These:O, sub-domains:O, simulate:O, sub-sections:O, of:O, the:O, main:O, newspapers:B-Idus, in:O, Spain:B-Area, plus:O, some:O, international:O, ones:O, like:O, the:O, Guardian:O, and:O, the:O, Washington:B-Org, Post:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The CVE-2012-0773 was originally discovered by VUPEN and has an interesting story .' [/INST] [The:O, CVE-2012-0773:B-Exp, was:O, originally:O, discovered:O, by:O, VUPEN:O, and:O, has:O, an:O, interesting:O, story:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In other words , the attackers attracted our attention by attempting to exploit Kaspersky Lab products .' [/INST] [In:O, other:O, words:O, ,:O, the:O, attackers:O, attracted:O, our:O, attention:O, by:O, attempting:O, to:O, exploit:O, Kaspersky:B-Tool, Lab:I-Tool, products:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We initially became aware of Careto when we observed attempts to exploit a vulnerability in our products to make the malware , invisible , in the system .' [/INST] [We:O, initially:O, became:O, aware:O, of:O, Careto:B-SamFile, when:O, we:O, observed:O, attempts:O, to:O, exploit:O, a:O, vulnerability:O, in:O, our:O, products:O, to:O, make:O, the:O, malware:O, ,:O, invisible:O, ,:O, in:O, the:O, system:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Most modules were created in 2012 .' [/INST] [Most:O, modules:O, were:O, created:O, in:O, 2012:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The attackers began taking them offline in January 2014 .' [/INST] [The:O, attackers:O, began:O, taking:O, them:O, offline:O, in:O, January:B-Time, 2014:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Last week we discussed Numbered Panda , a group that is also based out of China and is fairly well known to the security community , though by many names .' [/INST] [Last:O, week:O, we:O, discussed:O, Numbered:B-HackOrg, Panda:I-HackOrg, ,:O, a:O, group:O, that:O, is:O, also:O, based:O, out:O, of:O, China:B-Area, and:O, is:O, fairly:O, well:O, known:O, to:O, the:O, security:B-SecTeam, community:I-SecTeam, ,:O, though:O, by:O, many:O, names:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We revealed a Chinese-based adversary we crypt as Anchor Panda , a group with very specific tactics , techniques , and procedures ( TTPs ) and a keen interest in maritime operations and naval and aerospace technology .' [/INST] [We:O, revealed:O, a:O, Chinese-based:B-Area, adversary:O, we:O, crypt:O, as:O, Anchor:B-HackOrg, Panda:I-HackOrg, ,:O, a:O, group:O, with:O, very:O, specific:O, tactics:O, ,:O, techniques:O, ,:O, and:O, procedures:O, (:O, TTPs:O, ):O, and:O, a:O, keen:O, interest:O, in:O, maritime:O, operations:O, and:O, naval:B-Idus, and:O, aerospace:B-Idus, technology:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The campaign was active until January 2014 , but during our investigations the C&C servers were shut down .' [/INST] [The:O, campaign:B-OffAct, was:O, active:O, until:O, January:B-Time, 2014:I-Time, ,:O, but:O, during:O, our:O, investigations:O, the:O, C&C:O, servers:O, were:O, shut:O, down:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This week we are going to discuss Clever Kitten , whom , by virtue of several indicators , we have affiliated with the Islamic Republic of Iran .' [/INST] [This:O, week:O, we:O, are:O, going:O, to:O, discuss:O, Clever:O, Kitten:O, ,:O, whom:O, ,:O, by:O, virtue:O, of:O, several:O, indicators:O, ,:O, we:O, have:O, affiliated:O, with:O, the:O, Islamic:B-Area, Republic:I-Area, of:I-Area, Iran:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Clever Kitten has moved to leveraging strategic web compromises .' [/INST] [Clever:B-HackOrg, Kitten:I-HackOrg, has:O, moved:O, to:O, leveraging:O, strategic:B-Way, web:I-Way, compromises:I-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Clever Kitten actors have a strong affinity for PHP server-side attacks to make access ; this is relatively unique amongst targeted attackers who often favor targeting a specific individual at a specific organization using social engineering .' [/INST] [Clever:B-HackOrg, Kitten:I-HackOrg, actors:O, have:O, a:O, strong:O, affinity:O, for:O, PHP:O, server-side:O, attacks:B-OffAct, to:O, make:O, access:O, ;:O, this:O, is:O, relatively:O, unique:O, amongst:O, targeted:O, attackers:O, who:O, often:O, favor:O, targeting:O, a:O, specific:O, individual:B-Org, at:O, a:O, specific:O, organization:O, using:O, social:B-Idus, engineering:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Clever Kitten primarily targets global companies with strategic importance to countries that are contrary to Iranian interests .' [/INST] [Clever:B-HackOrg, Kitten:I-HackOrg, primarily:O, targets:O, global:O, companies:O, with:O, strategic:O, importance:O, to:O, countries:O, that:O, are:O, contrary:O, to:O, Iranian:O, interests:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'A Clever Kitten attack starts with the use of a web vulnerability scanner to conduct reconnaissance .' [/INST] [A:O, Clever:B-HackOrg, Kitten:I-HackOrg, attack:B-OffAct, starts:O, with:O, the:O, use:O, of:O, a:O, web:B-Tool, vulnerability:I-Tool, scanner:I-Tool, to:O, conduct:O, reconnaissance:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The scanner was identified as the Acunetix Web Vulnerability Scanner which is a commercial penetration testing tool that is readily available as a 14-day trial .' [/INST] [The:O, scanner:O, was:O, identified:O, as:O, the:O, Acunetix:B-SamFile, Web:I-SamFile, Vulnerability:I-SamFile, Scanner:I-SamFile, which:O, is:O, a:O, commercial:O, penetration:O, testing:O, tool:O, that:O, is:O, readily:O, available:O, as:O, a:O, 14-day:O, trial:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Once an exploitable page is identified , Clever Kitten will attempt to upload a PHP backdoor to gain remote access to the system .' [/INST] [Once:O, an:O, exploitable:O, page:O, is:O, identified:O, ,:O, Clever:O, Kitten:O, will:O, attempt:O, to:O, upload:O, a:O, PHP:O, backdoor:O, to:O, gain:B-Purp, remote:I-Purp, access:I-Purp, to:I-Purp, the:I-Purp, system:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The reason for this is likely the availability of exploits against web browsers , which for a variety of reasons allows an attacker to bypass security features such as Data Execution Prevention ( DEP ) or Address Space Layout Randomization ( ASLR ) .' [/INST] [The:O, reason:O, for:O, this:O, is:O, likely:O, the:O, availability:O, of:O, exploits:O, against:O, web:O, browsers:O, ,:O, which:O, for:O, a:O, variety:O, of:O, reasons:O, allows:O, an:O, attacker:O, to:O, bypass:O, security:O, features:O, such:O, as:O, Data:O, Execution:O, Prevention:O, (:O, DEP:O, ):O, or:O, Address:O, Space:O, Layout:O, Randomization:O, (:O, ASLR:O, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Once an exploitable page is identified , the actor will attempt to upload a PHP backdoor to gain remote access to the system .' [/INST] [Once:O, an:O, exploitable:O, page:O, is:O, identified:O, ,:O, the:O, actor:O, will:O, attempt:O, to:O, upload:O, a:O, PHP:O, backdoor:O, to:O, gain:B-Purp, remote:I-Purp, access:I-Purp, to:I-Purp, the:I-Purp, system:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In Clever Kitten 's attacks , the goal is lateral movement ; this is an attempt to move further into the target environment in order to begin intelligence collection .' [/INST] [In:O, Clever:O, Kitten:O, 's:O, attacks:B-OffAct, ,:O, the:O, goal:O, is:O, lateral:O, movement:O, ;:O, this:O, is:O, an:O, attempt:O, to:O, move:O, further:O, into:O, the:O, target:O, environment:O, in:O, order:O, to:O, begin:O, intelligence:B-Purp, collection:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This activity is a longer tail for the actor than a spearphish ; this is likely based on the Clever Kitten background , which may be focused on web development/application testing .' [/INST] [This:O, activity:B-OffAct, is:O, a:O, longer:O, tail:O, for:O, the:O, actor:O, than:O, a:O, spearphish:B-Way, ;:O, this:O, is:O, likely:O, based:O, on:O, the:O, Clever:O, Kitten:O, background:O, ,:O, which:O, may:O, be:O, focused:O, on:O, web:O, development/application:O, testing:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Without going too deep into the rabbit hole , there are several indicators pointing to an Iranian nexus , including language artifacts in the tool-marks used by the attacker , as well as network activity tying this actor to a very specific location that we have high confidence in not being spoofed .' [/INST] [Without:O, going:O, too:O, deep:O, into:O, the:O, rabbit:O, hole:O, ,:O, there:O, are:O, several:O, indicators:O, pointing:O, to:O, an:O, Iranian:O, nexus:O, ,:O, including:O, language:O, artifacts:O, in:O, the:O, tool-marks:O, used:O, by:O, the:O, attacker:O, ,:O, as:O, well:O, as:O, network:B-OffAct, activity:I-OffAct, tying:O, this:O, actor:O, to:O, a:O, very:O, specific:O, location:O, that:O, we:O, have:O, high:O, confidence:O, in:O, not:O, being:O, spoofed:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Clever Kitten 's goal is to eventually be able to masquerade as a legitimate user by compromising credentials either through a pass-the-hash attack , or by dumping password hashes from a compromised host .' [/INST] [Clever:B-HackOrg, Kitten:I-HackOrg, 's:O, goal:O, is:O, to:O, eventually:O, be:O, able:O, to:O, masquerade:O, as:O, a:O, legitimate:O, user:O, by:O, compromising:O, credentials:O, either:O, through:O, a:O, pass-the-hash:B-OffAct, attack:I-OffAct, ,:O, or:O, by:O, dumping:O, password:O, hashes:O, from:O, a:O, compromised:O, host:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The campaign targets Middle Eastern organizations largely from the Lebanon and United Arab Emirates , though , Indian and Canadian companies with interests in those Middle Eastern countries are also targeted .' [/INST] [The:O, campaign:B-OffAct, targets:O, Middle:B-Area, Eastern:I-Area, organizations:O, largely:O, from:O, the:O, Lebanon:B-Area, and:O, United:B-Area, Arab:B-Org, Emirates:B-Org, ,:O, though:O, ,:O, Indian:B-Area, and:O, Canadian:B-Area, companies:O, with:O, interests:O, in:O, those:O, Middle:B-Area, Eastern:I-Area, countries:O, are:O, also:O, targeted:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'There are new TTPs used in this attack – for example Agent_Drable is leveraging the Django python framework for command and control infrastructure , the technical details of which are outlined later in the blog .' [/INST] [There:O, are:O, new:O, TTPs:O, used:O, in:O, this:O, attack:B-OffAct, –:O, for:O, example:O, Agent_Drable:O, is:O, leveraging:O, the:O, Django:B-Tool, python:O, framework:O, for:O, command:O, and:O, control:O, infrastructure:O, ,:O, the:O, technical:O, details:O, of:O, which:O, are:O, outlined:O, later:O, in:O, the:O, blog:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'n summary , Cold River is a sophisticated threat actor making malicious use of DNS tunneling for command and control activities , compelling lure documents , and previously unknown implants .' [/INST] [n:O, summary:O, ,:O, Cold:O, River:O, is:O, a:O, sophisticated:O, threat:O, actor:O, making:O, malicious:O, use:O, of:O, DNS:B-Tool, tunneling:I-Tool, for:O, command:B-OffAct, and:I-OffAct, control:I-OffAct, activities:I-OffAct, ,:O, compelling:O, lure:O, documents:O, ,:O, and:O, previously:O, unknown:O, implants:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Some of the exploit server paths contain modules that appear to have been designed to infect Linux computers , but we have not yet located the Linux backdoor .' [/INST] [Some:O, of:O, the:O, exploit:O, server:O, paths:O, contain:O, modules:O, that:O, appear:O, to:O, have:O, been:O, designed:O, to:O, infect:O, Linux:B-Org, computers:I-Org, ,:O, but:O, we:O, have:O, not:O, yet:O, located:O, the:O, Linux:O, backdoor:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The campaign targets Middle Eastern organizations largely from the Lebanon and United Arab Emirates , though , Indian and Canadian companies with interests in those Middle Eastern countries may have also been targeted .' [/INST] [The:O, campaign:B-OffAct, targets:O, Middle:O, Eastern:O, organizations:O, largely:O, from:O, the:O, Lebanon:B-Area, and:O, United:B-Area, Arab:B-Org, Emirates:I-Org, ,:O, though:O, ,:O, Indian:B-Area, and:O, Canadian:B-Area, companies:O, with:O, interests:O, in:O, those:O, Middle:B-Area, Eastern:I-Area, countries:O, may:O, have:O, also:O, been:O, targeted:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The decoy documents used by the InPage exploits suggest that the targets are likely to be politically or militarily motivated .' [/INST] [The:O, decoy:B-Tool, documents:I-Tool, used:O, by:O, the:O, InPage:B-Exp, exploits:I-Exp, suggest:O, that:O, the:O, targets:O, are:O, likely:O, to:O, be:O, politically:B-Idus, or:O, militarily:B-Idus, motivated:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The use of InPage as an attack vector is not commonly seen , with the only previously noted attacks being documented by Kaspersky in late 2016 .' [/INST] [The:O, use:O, of:O, InPage:B-Tool, as:O, an:O, attack:B-OffAct, vector:O, is:O, not:O, commonly:O, seen:O, ,:O, with:O, the:O, only:O, previously:O, noted:O, attacks:B-OffAct, being:O, documented:O, by:O, Kaspersky:B-SecTeam, in:O, late:B-Time, 2016:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The decoy documents dropped suggest that the targets are likely to be politically or militarily motivated , with subjects such as Intelligence reports and political situations being used as lure documents .' [/INST] [The:O, decoy:B-SamFile, documents:I-SamFile, dropped:O, suggest:O, that:O, the:O, targets:O, are:O, likely:O, to:O, be:O, politically:B-Idus, or:O, militarily:B-Idus, motivated:O, ,:O, with:O, subjects:O, such:O, as:O, Intelligence:O, reports:O, and:O, political:B-Idus, situations:O, being:O, used:O, as:O, lure:O, documents:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While documents designed to exploit the InPage software are rare , they are not new – however in recent weeks Unit42 has observed numerous InPage exploits leveraging similar shellcode , suggesting continued use of the exploit previously discussed by Kaspersky .' [/INST] [While:O, documents:O, designed:O, to:O, exploit:O, the:O, InPage:B-Tool, software:I-Tool, are:O, rare:O, ,:O, they:O, are:O, not:O, new:O, –:O, however:O, in:O, recent:O, weeks:O, Unit42:B-SecTeam, has:O, observed:O, numerous:O, InPage:B-Exp, exploits:I-Exp, leveraging:O, similar:O, shellcode:O, ,:O, suggesting:O, continued:O, use:O, of:O, the:O, exploit:O, previously:O, discussed:O, by:O, Kaspersky:B-SecTeam, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Confucius targeted a particular set of individuals in South Asian countries , such as military personnel and businessmen , among others .' [/INST] [Confucius:O, targeted:O, a:O, particular:O, set:O, of:O, individuals:O, in:O, South:O, Asian:O, countries:O, ,:O, such:O, as:O, military:B-Org, personnel:I-Org, and:O, businessmen:B-Org, ,:O, among:O, others:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Tweety Chat 's Android version can record audio , too .' [/INST] [Tweety:B-Tool, Chat:I-Tool, 's:O, Android:O, version:O, can:O, record:B-Features, audio:I-Features, ,:O, too:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Confucius' operations include deploying bespoke backdoors and stealing files from their victim 's systems with tailored file stealers , some of which bore resemblances to Patchwork 's .' [/INST] [Confucius':O, operations:O, include:O, deploying:B-Purp, bespoke:I-Purp, backdoors:I-Purp, and:O, stealing:B-Purp, files:I-Purp, from:O, their:O, victim:O, 's:O, systems:O, with:O, tailored:O, file:O, stealers:O, ,:O, some:O, of:O, which:O, bore:O, resemblances:O, to:O, Patchwork:B-HackOrg, 's:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Compared to Patchwork , whose Trojanized documents exploit at least five security flaws , Confucius' backdoors are delivered through Office files exploiting memory corruption vulnerabilities CVE-2015-1641 and CVE-2017-11882 .' [/INST] [Compared:O, to:O, Patchwork:B-HackOrg, ,:O, whose:O, Trojanized:O, documents:O, exploit:O, at:O, least:O, five:O, security:O, flaws:O, ,:O, Confucius':O, backdoors:O, are:O, delivered:O, through:O, Office:O, files:O, exploiting:O, memory:O, corruption:O, vulnerabilities:O, CVE-2015-1641:B-Exp, and:O, CVE-2017-11882:B-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Back in February , we noted the similarities between the Patchwork and Confucius groups and found that , in addition to the similarities in their malware code , both groups primarily went after targets in South Asia .' [/INST] [Back:O, in:O, February:O, ,:O, we:O, noted:O, the:O, similarities:O, between:O, the:O, Patchwork:B-HackOrg, and:O, Confucius:B-HackOrg, groups:I-HackOrg, and:O, found:O, that:O, ,:O, in:O, addition:O, to:O, the:O, similarities:O, in:O, their:O, malware:O, code:O, ,:O, both:O, groups:O, primarily:O, went:O, after:O, targets:O, in:O, South:B-Area, Asia:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Back in February , Trend Micro noted the similarities between the Patchwork and Confucius groups and found that , in addition to the similarities in their malware code , both groups primarily went after targets in South Asia .' [/INST] [Back:O, in:O, February:B-Time, ,:O, Trend:B-SecTeam, Micro:I-SecTeam, noted:O, the:O, similarities:O, between:O, the:O, Patchwork:B-HackOrg, and:O, Confucius:B-HackOrg, groups:I-HackOrg, and:O, found:O, that:O, ,:O, in:O, addition:O, to:O, the:O, similarities:O, in:O, their:O, malware:O, code:O, ,:O, both:O, groups:O, primarily:O, went:O, after:O, targets:O, in:O, South:B-Area, Asia:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'One of its file stealers , swissknife2 , abuses a cloud storage service as a repository of exfiltrated files .' [/INST] [One:O, of:O, its:O, file:O, stealers:O, ,:O, swissknife2:B-Tool, ,:O, abuses:B-Features, a:I-Features, cloud:I-Features, storage:I-Features, service:I-Features, as:O, a:O, repository:O, of:O, exfiltrated:O, files:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'During the months that followed in which we tracked Confucius' activities , we found that they were still aiming for Pakistani targets .' [/INST] [During:O, the:O, months:O, that:O, followed:O, in:O, which:O, we:O, tracked:O, Confucius':B-OffAct, activities:I-OffAct, ,:O, we:O, found:O, that:O, they:O, were:O, still:O, aiming:O, for:O, Pakistani:O, targets:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'During their previous campaign , we found Confucius using fake romance websites to entice victims into installing malicious Android applications .' [/INST] [During:O, their:O, previous:O, campaign:B-OffAct, ,:O, we:O, found:O, Confucius:O, using:O, fake:O, romance:O, websites:O, to:O, entice:O, victims:O, into:O, installing:O, malicious:O, Android:O, applications:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Periodically , the malware tries to contact the Command-and-Control ( C&C ) server with the username encoded into parameters .' [/INST] [Periodically:O, ,:O, the:O, malware:O, tries:O, to:O, contact:O, the:O, Command-and-Control:B-Tool, (:O, C&C:O, ):O, server:O, with:O, the:O, username:O, encoded:O, into:O, parameters:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This function is similar to the various versions of backdoors ( such as sctrls and sip_telephone ) that we analyzed in our previous blog post and whitepaper .' [/INST] [This:O, function:O, is:O, similar:O, to:O, the:O, various:O, versions:O, of:O, backdoors:O, (:O, such:O, as:O, sctrls:B-Tool, and:O, sip_telephone:B-Tool, ):O, that:O, we:O, analyzed:O, in:O, our:O, previous:O, blog:O, post:O, and:O, whitepaper:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This algorithm was previously discussed by security researchers in a Confucius-related blog post .' [/INST] [This:O, algorithm:O, was:O, previously:O, discussed:O, by:O, security:O, researchers:O, in:O, a:O, Confucius-related:O, blog:O, post:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Lately , Patchwork has been sending multiple RTF files exploiting CVE-2017-8570 .' [/INST] [Lately:O, ,:O, Patchwork:B-HackOrg, has:O, been:O, sending:O, multiple:O, RTF:B-SamFile, files:I-SamFile, exploiting:O, CVE-2017-8570:B-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The group still uses the Badnews malware , a backdoor with information-stealing and file-executing capabilities , albeit updated with a slight modification in the encryption routine at the end of 2017 , when they added Blowfish encryption on top of their custom encryption described in our former Patchwork blogpost .' [/INST] [The:O, group:O, still:O, uses:O, the:O, Badnews:B-Tool, malware:I-Tool, ,:O, a:O, backdoor:O, with:O, information-stealing:O, and:O, file-executing:O, capabilities:O, ,:O, albeit:O, updated:O, with:O, a:O, slight:O, modification:O, in:O, the:O, encryption:O, routine:O, at:O, the:O, end:O, of:O, 2017:B-Time, ,:O, when:O, they:O, added:O, Blowfish:O, encryption:O, on:O, top:O, of:O, their:O, custom:O, encryption:O, described:O, in:O, our:O, former:O, Patchwork:B-HackOrg, blogpost:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Threat actors like Confucius and Patchwork are known for their large arsenal of tools and ever-evolving techniques that can render traditional security solutions — which are often not designed to handle the persistent and sophisticated threats detailed in this blog — ineffective .' [/INST] [Threat:O, actors:O, like:O, Confucius:B-HackOrg, and:O, Patchwork:B-HackOrg, are:O, known:O, for:O, their:O, large:O, arsenal:O, of:O, tools:O, and:O, ever-evolving:O, techniques:O, that:O, can:O, render:B-Purp, traditional:I-Purp, security:I-Purp, solutions:I-Purp, —:O, which:O, are:O, often:O, not:O, designed:O, to:O, handle:O, the:O, persistent:O, and:O, sophisticated:O, threats:O, detailed:O, in:O, this:O, blog:O, —:O, ineffective:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The reality is that IT departments of small to large-sized organizations are not equipped to handle the more advanced threats that groups like Confucius use in their attacks .' [/INST] [The:O, reality:O, is:O, that:O, IT:B-Org, departments:I-Org, of:O, small:O, to:O, large-sized:O, organizations:O, are:O, not:O, equipped:O, to:O, handle:O, the:O, more:O, advanced:O, threats:O, that:O, groups:O, like:O, Confucius:O, use:O, in:O, their:O, attacks:B-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Patchwork uses email as an entry point , which is why securing the email gateway is important .' [/INST] [Patchwork:B-HackOrg, uses:O, email:B-Way, as:O, an:O, entry:O, point:O, ,:O, which:O, is:O, why:O, securing:O, the:O, email:B-Way, gateway:I-Way, is:O, important:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This blog post examines two similar malware families that utilize the aforementioned technique to abuse legitimate websites , their connections to each other , and their connections to known espionage campaigns .' [/INST] [This:O, blog:O, post:O, examines:O, two:O, similar:O, malware:O, families:O, that:O, utilize:O, the:O, aforementioned:O, technique:O, to:O, abuse:O, legitimate:O, websites:O, ,:O, their:O, connections:O, to:O, each:O, other:O, ,:O, and:O, their:O, connections:O, to:O, known:O, espionage:B-OffAct, campaigns:I-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In order to increase the likelihood of their malware successfully communicating home , cyber espionage threat actors are increasingly abusing legitimate web services , in lieu of DNS lookups to retrieve a command and control address .' [/INST] [In:O, order:O, to:O, increase:B-Purp, the:I-Purp, likelihood:I-Purp, of:O, their:O, malware:O, successfully:O, communicating:O, home:O, ,:O, cyber:O, espionage:O, threat:O, actors:O, are:O, increasingly:O, abusing:B-Way, legitimate:I-Way, web:I-Way, services:I-Way, ,:O, in:O, lieu:O, of:O, DNS:B-Way, lookups:I-Way, to:O, retrieve:O, a:O, command:O, and:O, control:O, address:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In 2013 , Rapid7 reported on a series of relatively amateur attacks against Pakistani targets .' [/INST] [In:O, 2013:B-Time, ,:O, Rapid7:B-SecTeam, reported:O, on:O, a:O, series:O, of:O, relatively:O, amateur:O, attacks:B-OffAct, against:O, Pakistani:O, targets:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The first of which we call ' CONFUCIUS_A ' , a malware family that has links to a series of attacks associated with a backdoor attack method commonly known as SNEEPY ( aka ByeByeShell ) first reported by Rapid7 in 2013 .' [/INST] [The:O, first:O, of:O, which:O, we:O, call:O, ':O, CONFUCIUS_A:B-SamFile, ':O, ,:O, a:O, malware:O, family:O, that:O, has:O, links:O, to:O, a:O, series:O, of:O, attacks:B-OffAct, associated:O, with:O, a:O, backdoor:B-OffAct, attack:I-OffAct, method:O, commonly:O, known:O, as:O, SNEEPY:B-Tool, (:O, aka:O, ByeByeShell:B-Tool, ):O, first:O, reported:O, by:O, Rapid7:B-SecTeam, in:O, 2013:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'At first glance CONFUCIUS_B looks very similar to CONFUCIUS_A , and they are also packaged in plain SFX binary files .' [/INST] [At:O, first:O, glance:O, CONFUCIUS_B:B-SamFile, looks:O, very:O, similar:O, to:O, CONFUCIUS_A:B-SamFile, ,:O, and:O, they:O, are:O, also:O, packaged:O, in:O, plain:O, SFX:B-Tool, binary:I-Tool, files:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The CONFUCIUS_B executable is disguised as a PowerPoint presentation , using a Right-To-Left-Override ( RTLO ) trick and a false icon .' [/INST] [The:O, CONFUCIUS_B:B-SamFile, executable:O, is:O, disguised:B-Features, as:I-Features, a:I-Features, PowerPoint:I-Features, presentation:I-Features, ,:O, using:B-Features, a:I-Features, Right-To-Left-Override:I-Features, (:O, RTLO:B-Tool, ):O, trick:O, and:O, a:O, false:B-Features, icon:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We also believe that both clusters of activity have links to attacks with likely Indian origins , the CONFUCIUS_A attacks are linked to the use of SNEEPY/BYEBYESHELL and the CONFUCIUS_B have a loose link to Hangover .' [/INST] [We:O, also:O, believe:O, that:O, both:O, clusters:O, of:O, activity:B-OffAct, have:O, links:O, to:O, attacks:B-OffAct, with:O, likely:O, Indian:O, origins:O, ,:O, the:O, CONFUCIUS_A:B-OffAct, attacks:I-OffAct, are:O, linked:O, to:O, the:O, use:O, of:O, SNEEPY/BYEBYESHELL:B-Tool, and:O, the:O, CONFUCIUS_B:B-SamFile, have:O, a:O, loose:O, link:O, to:O, Hangover:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The two malware families themselves are also very similar , and therefore we think that the shared technique is an indication of a single developer , or development company , behind both CONFUCIUS_A and CONFUCIUS_B .' [/INST] [The:O, two:O, malware:O, families:O, themselves:O, are:O, also:O, very:O, similar:O, ,:O, and:O, therefore:O, we:O, think:O, that:O, the:O, shared:O, technique:O, is:O, an:O, indication:O, of:O, a:O, single:O, developer:O, ,:O, or:O, development:B-Org, company:I-Org, ,:O, behind:O, both:O, CONFUCIUS_A:B-SamFile, and:O, CONFUCIUS_B:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this blog post , we discussed two separate malware variations that behave in very similar ways and use similar techniques to acquire a C2 address , with both using Yahoo Answers and Quora to evade traditional mechanisms for blocking command and control domains .' [/INST] [In:O, this:O, blog:O, post:O, ,:O, we:O, discussed:O, two:O, separate:O, malware:O, variations:O, that:O, behave:O, in:O, very:O, similar:O, ways:O, and:O, use:O, similar:O, techniques:O, to:O, acquire:O, a:O, C2:O, address:O, ,:O, with:O, both:O, using:O, Yahoo:O, Answers:O, and:O, Quora:O, to:O, evade:O, traditional:O, mechanisms:O, for:O, blocking:O, command:O, and:O, control:O, domains:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Android version , for instance , can steal SMS messages , accounts , contacts , and files , as well as record audio .' [/INST] [The:O, Android:B-SamFile, version:I-SamFile, ,:O, for:O, instance:O, ,:O, can:O, steal:B-Features, SMS:I-Features, messages:I-Features, ,:O, accounts:B-Features, ,:O, contacts:B-Features, ,:O, and:O, files:B-Features, ,:O, as:O, well:O, as:O, record:B-Features, audio:I-Features, .:O] </s> |
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